Design of experiment and montecarlo simulation as support for gas turbine power plant availabilty estimation

Maintenance is an important aspect in order to guarantee the efficiency of industrial facilities. For power plants the high availability ratios can be obtained only with preventive maintenance but the result costs increases rapidly. In order to reduce the cost level of the maintenance activity, on-condition maintenance is carried out on an increasing subset of components. Only using appropriate reliability models can identify the optimal mix between preventive and on-condition maintenance. Some time the data required by such models are inadequate or missing and the performances of the implemented system can fall quite rapidly. The authors propose an innovative approach based on a hierarchical Montecarlo simulator able to estimate properly the power plant reliability and, at the same time, improve its performances by a fine-tuning of its parameters. A real life case study is than presented and discussed.